Abstract

   Despite considerable progress in understanding the pathogenesis of
   Mycobacterium tuberculosis (Mtb), development of new therapeutics and
   vaccines against it has proven difficult. This is at least in part due
   to the use of less than optimal models of in-vivo Mtb infection, which
   has precluded a study of the physiology of the pathogen in niches where
   it actually persists. C3HeB/FeJ (Kramnik) mice develop human-like
   lesions when experimentally infected with Mtb and thus make available,
   a faithful and highly tractable system to study the physiology of the
   pathogen in-vivo. We compared the transcriptomics of Mtb and various
   mutants in the DosR (DevR) regulon derived from Kramnik mouse
   granulomas to those cultured in-vitro. We recently showed that mutant
   ΔdosS is attenuated in C3HeB/FeJ mice. Aerosol exposure of mice with
   the mutant mycobacteria resulted in a substantially different and a
   relatively weaker transcriptional response (< = 20 genes were induced)
   for the functional category ‘Information Pathways’ in Mtb:ΔdosR; ‘Lipid
   Metabolism’ in Mtb:ΔdosT; ‘Virulence, Detoxification, Adaptation’ in
   both Mtb:ΔdosR and Mtb:ΔdosT; and ‘PE/PPE’ family in all mutant strains
   compare to wild-type Mtb H37Rv, suggesting that the inability to induce
   DosR functions to different levels can modulate the interaction of the
   pathogen with the host. The Mtb genes expressed during growth in
   C3HeB/FeJ mice appear to reflect adaptation to differential nutrient
   utilization for survival in mouse lungs. The genes such as glnB,
   Rv0744c, Rv3281, sdhD/B, mce4A, dctA etc. downregulated in mutant ΔdosS
   indicate their requirement for bacterial growth and flow of
   carbon/energy source from host cells. We conclude that genes expressed
   in Mtb during in-vivo chronic phase of infection in Kramnik mice mainly
   contribute to growth, cell wall processes, lipid metabolism, and
   virulence.

Introduction

   Delineating mycobacterial gene expression in-vivo is central to the
   understanding how bacilli invade and interact with or disrupt host cell
   functions, to facilitate their adaptation to different
   microenvironments [[27]1–[28]7]. A clear understanding of the molecular
   events responsible for establishing and maintaining Mtb infection is
   thus essential to develop approaches to contain the disease. However,
   this requires the use of faithful models of human Mtb infection. The
   traditional mouse model does not result in the formation of human-like
   granulomas upon experimental infection [[29]8]. For example, C57Bl/6
   mice do not faithfully reproduce certain aspects of human TB. In
   contrast, C3HeB/FeJ mice display lesions with prominent necrotic
   degeneration, thus more closely resembling human granulomas
   [[30]9–[31]11]. It has been previously demonstrated that tubercle
   lesions in C3HeB/FeJ mice develop hypoxia [[32]10–[33]12]. This results
   in the induction of the DosR regulon that likely enables Mtb to persist
   in hypoxic conditions [[34]13, [35]14] and within human-like lesions
   present in the lungs of Mtb infected non-human primates [[36]15].
   Induction of DosR and the resulting downstream transcriptional changes
   then likely cause significant perturbation in the metabolic profile of
   the pathogen. It is postulated that this not only assists the survival
   of Mtb in the changed milieu, allowing it to conserve energy while
   remaining viable in an anorexic environment, but likely also results in
   altered antigen presentation [[37]16, [38]17] and thus adaptive
   responses [[39]15]. Such changes likely impact significantly, the
   ability of the antigen-specific responses to control Mtb replication
   and might facilitate the persistence of the pathogen over the
   long-haul. Therefore, we tested the regulation of Mtb genes by
   comparing the transcription profile that investigated the effects of TB
   infection in C3HeB/FeJ mice.

   Here we report expression profiles of mycobacterial genes upon
   infection of C3HeB/FeJ mice with Mtb H37Rv wild-type (WT) (henceforth
   referred to as Mtb) relative to the mutants defective in response
   regulator DosR (Mtb:ΔdosR) or sensor kinases DosS (Mtb:ΔdosS) or DosT
   (Mtb:ΔdosT) during chronic phase of infection in C3HeB/FeJ mice by
   using DNA microarrays.

Materials and Methods

Bacterial Strains and Animals

   We used frozen lung samples of C3HeB/FeJ mice from a previous study
   [[40]11]. The Mtb and Dos mutants were revived from frozen stocks and
   cultured as described [[41]18].

In-Situ RNA Hybridization

   In-situ RNA-RNA hybridizations designed to detect mycobacteria specific
   transcripts on 5 μm section of paraffin-embedded lung tissue
   (RNase-free) with appropriate controls were performed essentially as
   described earlier [[42]19].

Preparation of RNA samples

   RNA was isolated from frozen lung samples from our previous study
   [[43]11]. Frozen tissue (15–20 mg lung lobe of mice) samples were
   placed in a sterile plastic tissue sample bag, crushed mechanically,
   transferred to screw caped tube containing 700 μl Qiazol (Qiazen,
   Germany), followed by mixing the contents and incubated at room temp
   for 10 minutes. The samples were lysed by bead beating in Lysing Matrix
   B tubes (MP Biomedicals, USA), added with 140 μl chloroform and mixed
   by inverting the tubes several time followed by incubation for 5 min at
   room temp and centrifugation at 13,000 rpm for 15 min at 4°C. RNA was
   purified with RNA purification kit (Qiazen, Germany) and used in
   microarrays as described [[44]18]. RNA was isolated from in-vitro grown
   Mtb cultures as described [[45]20].

RNA Quantification and Real Time PCR

   The amount of total RNA from in-vitro and in-vivo samples used for each
   hybridization was quantified first by RT-PCR as previously described
   [[46]21]. Toward this, total RNA isolated from lung tissue was
   subjected to microbe enrichment kit for removal of host RNA followed by
   microbe express and bacterial RNA amplification, strictly as per
   manufacturer’s instructions (Life Technologies, USA). RNA isolated from
   in-vitro grown cultures was also treated with microbe express and
   amplified in parallel. RT-PCR was carried out with cDNA that was
   reverse transcribed from 1000 ng DNA-free RNA as described [[47]21].
   For quantification, a series of genomic DNA with 10-fold dilution was
   used in RT-PCR as described [[48]21]. Constitutive sigA mRNA was
   quantified in all samples and used as invariable housekeeping control
   in RT-PCR. The data was normalized to sigA. We also tested the levels
   of dnaB in Mtb and Dos mutants grown in-vitro or those isolated from
   mouse lung samples.

DNA Microarrays and Sample hybridization

   Mtb specific DNA microarrays (MYcroarrays, Biodiscovery Llc, USA) were
   used to compare transcriptome-wide responses in WT Mtb and the Dos
   mutant strains isolated from mouse lung samples from our previous study
   [[49]11]. Detailed protocols for array procedures have been described
   earlier [[50]22]. Differences in the magnitude of gene expression
   relative to cultures grown till log phase were subjected to statistical
   analysis using corrected ANOVA (P<0.05) in 2 biological replicate
   arrays and in every technical replicate spot on each array. Real-time
   (RT) PCR was performed as previously described [[51]20]. The gene
   expression levels were normalized to sigA. The microarray data has been
   assigned a GEO (Gene Expression Omnibus) and is publicly available
   using the accession number [52]GSE70765.

Comparative transcriptomics

   We compared our current data on Mtb gene-expression using DNA
   microarray technology, to that obtained previously from BALB/c mice
   [[53]7]), macrophages [[54]23]) and in-vitro (NRP) conditions
   [[55]24]). First, we collected all the genes (1.5-fold with increased
   or decreased expression in datasets obtained from Kramnik mice in the
   current study and compared these to the datasets (gene expression
   values in fold-change) obtained during growth in BALB/c mice,
   macrophages and in-vitro (NRP) conditions. The fold-change in gene
   expression was plotted against mycobacterial genes obtained from
   various datasets.

Results

Detection of RNA in the infected lungs of C3HeB/FeJ mice

   Quantitative RT-PCR on amplified RNA samples derived from Mtb-,
   Mtb:ΔdosR-, Mtb:ΔdosS- and Mtb:ΔdosT-infected mouse lungs at the
   chronic stage of infection (frozen lung samples were derived from a
   prior in-vivo study [[56]11]) exhibited the presence of transcripts of
   gene sigA (not shown). sigA transcripts were also detected by In-Situ
   hybridization using a specific probe generated using the DIG-RNA
   labeling kit (Roche). Lung granulomas from Kramnik mice infected with
   Mtb and Dos mutants contained abundant sigA transcripts as visualized
   by brown signal ([57]Fig 1), although not all cells stained positive.
   On the contrary, the expression levels of dnaB did not exhibit induced
   expression, when assayed by RT-PCR (not shown). Together, these two
   results strongly suggest that Mtb sigA mRNA is expressed at high levels
   in infected lung lesions [[58]25].

Fig 1. In-Situ hybridization.

   [59]Fig 1
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   In-Situ hybridization detected the presence of Mtb specific sigA
   transcripts in mice lung samples (derived at chronic phase of
   infection) infected with Mtb, Mtb:ΔdosR, Mtb:ΔdosS and Mtb:ΔdosT
   strains. Representative images with low (left) and high (right)
   magnification for each Mtb strain is shown.

Functional analysis of Mtb genes expressed in C3HeB/FeJ mouse lungs

   We compared the changes in bacterial gene expression levels by
   microarray in WT Mtb and Dos mutant strains during chronic phase of
   in-vivo growth in C3HeB/FeJ mice. Total RNA was isolated and purified
   from mouse lung samples as well as from Mtb and Dos mutant strains
   cultured in-vitro. Prior to microarray analyses, purified RNA samples
   were enriched for bacterial mRNA, subjected to amplification and then
   normalized on the basis of the invariant gene-expression exhibited by
   sigA in both lung and in-vitro grown cultures by RT-PCR (not shown).
   For microarray experiments, RNA was isolated from lung, and profiled
   relative to the RNA isolated from control samples (in-vitro grown Mtb
   and Dos mutant cultures).

   Statistical analyses revealed that a group of 650, 255, 406 and 114
   mycobacterial genes whose expression state changed (up-/down-regulated)
   respectively for each Mtb, Mtb:ΔdosR, Mtb:ΔdosS and Mtb:ΔdosT ([61]Fig
   2A). We identified several differentially expressed genes between Mtb
   and Dos mutants in mouse lungs, which delineate various functional
   categories as defined in the “Tuberculist” database
   ([62]http://tuberculist.epfl.ch) ([63]Fig 2B–2C). The results in
   [64]Fig 2B–2C were calculated for a given data set, based on the total
   number of genes assigned to each category in the genome and then
   compared to the actual number of genes in a functional category induced
   or repressed for a Mtb strain. A group of genes involved in functional
   category ‘lipid metabolism’, ‘cell wall biosynthesis’ as well as those
   encoding various ‘regulatory’ and ‘virulence, detoxification,
   adaptation’ proteins etc. demonstrated statistically significant
   (P<0.05) differences in gene expression ([65]Fig 3 and [66]S1 Table).
   Various functional categories have been discussed below.

Fig 2. Functional categories with significant changes in gene expression in
DNA microarray and Mtb growth.

   [67]Fig 2
   [68]Open in a new tab

   A. The graph shows the total number of genes (left) changed in DNA
   microarray and mycobacterial colony-forming units (CFU) in mouse lungs
   during Mtb, Mtb:ΔdosR, Mtb:ΔdosS and Mtb:ΔdosT infection. B. Functional
   categories with significant changes in gene expression and number of
   genes either up or down (cut off 1.5 fold, P<0.05) are shown in each
   data set. C. Percentage of genes (obtained from panels A and B) is
   shown for each functional category.

Fig 3. Gene expression in C3HeB/FeJ mouse lungs.

   [69]Fig 3
   [70]Open in a new tab

   The unique genes (on X-axis) expressed (gene expression obtained in
   microarray using sigA normalized RNA of Mtb and Dos mutants derived
   from mouse lungs compared to in-vitro grown culture are shown on
   Y-axis) in C3HeB/FeJ mouse lungs infected with Mtb (red circle) or
   Mtb:ΔdosR (black diamond) or Mtb:ΔdosS (blue, upright triangle) or
   Mtb:ΔdosT (green, inverted triangle) are shown. Various functional
   categories are indicated according to the information available in the
   ‘Tuberculist’ database.

Information pathways

   DNA recombination and repair result in an increased mutation frequency
   and better adaptability of the bacterium to stressful conditions inside
   the host. Thus, genes involved in DNA damage, repair and recombination
   e.g. Rv3585, Rv0630c etc. changed in all datasets may indicate
   modification of mycobacterial genes in hostile environment. In
   addition, a set of genes required for DNA replication, transcription
   and translation processes were also upregulated; Rv0001, Rv0056,
   Rv0718, Rv0719, Rv2904 etc. in Mtb-; Rv3442c, Rv0233, Rv3585, Rv2889c
   etc. in Mtb:ΔdosR-; Rv1165, Rv2890c in Mtb:ΔdosS-; Rv0937c, Rv3585,
   Rv0630c in Mtb:ΔdosT-infected lung samples. The genes pks6 encoding a
   polyketide synthase and tgs2 (Rv0045c) encoding a putative
   triacylglycerol synthase (diacylglycerol acyltransferase) were also
   changed in Mtb WT, Mtb:ΔdosR and Mtb:ΔdosT datasets.

   It is known that Mtb gene products which are involved in the import of
   host-derived fatty acids and synthesis of tri-acyl glycerol (TAG) might
   play critical roles in the energy metabolism during dormant stage
   [[71]26]. Interestingly, among iVEGI (In-vivo Expressed Genomic Island)
   signature genes as described previously [[72]7] Rv0974c (1.8 fold up),
   Rv0976c (2.0 fold up) involved in lipid metabolism and Rv0996 (1.83
   fold) encoding a transmembrane protein involved in cell wall and cell
   processes also expressed in mice infected with Mtb. On the other hand
   fadE12 (Rv0972c, 1.62-fold upregulation) and Rv0992 (2.6-fold
   upregulation) involved in lipid metabolism and conserved hypothetical
   protein (unknown function) respectively were also changed in Mtb
   WT-infected lung samples only. In summary, the expression of different
   genes but those involved in lipid metabolism in all datasets indicate
   degradation of host-cell lipids is vital in the intracellular life of
   bacilli and host cells may provide potential precursors for various
   mycobacterial metabolic processes and cell wall constituents required
   during growth in C3HeB/FeJ mice. Genes involved in lipid metabolism
   were examined next.

Lipid metabolism

   In Mtb, the expression of fadD26 (Rv2930), involved in
   phthioceroldimycocerosate (PDIM) biosynthesis; fadE13 (Rv0975c),
   probable acyl-CoA dehydrogenase; ppsD (Rv2934) involved PDIM
   biosynthesis; fabG2 (Rv1350), echA9 (Rv071c) involved in the fatty acid
   biosynthesis and fadD5 (Rv0166) in lipid degradation was noted. In
   Mtb:ΔdosR, fadD22 (Rv2948c, 1.7 fold up) involved in biosynthesis of
   phenolic glycolipids (PGLs) and PDIM biosynthesis was upregulated.
   Similarly following genes involved in lipid metabolism (but different
   from WT Mtb dataset) were specifically demonstrated high expression in
   Mtb:ΔdosR infected samples; fadE26 (Rv3504), fadD36 (Rv1193) and fadE29
   (Rv3543c) involved in lipid degradation; fadE19 (Rv2005c), in fatty
   acids metabolism. In Mtb:ΔdosS-infected samples following genes of
   lipid metabolism pathway were expressed; fadE10 (Rv0873) encoding an
   acyl-CoA dehydrogenase involved in lipid degradation; fbpA (Rv3804c)
   necessary for cell wall mycolation and biogenesis of trehalose
   dimycolate (cord factor) and to maintain cell wall integrity; fadE22
   (Rv3061c) probable acyl-CoA dehydrogenase; pks9 (Rv1664) probable
   polyketide synthase; fas (Rv2524c) probable fatty acid synthase (fatty
   acid synthetase); echA7 (Rv0971c) probable enoyl-CoA hydratase; (enoyl
   hydrase) (unsaturated acyl-CoA hydratase) (crotonase); cdh (Rv2289)
   probable CDP-diacylglycerol pyrophosphatase (CDP-diacylglycerol
   diphosphatase) (CDP-diacylglycerol phosphatidylhydrolase). The gene
   papA3 (Rv1182) (encodes a polyketide synthase associated protein) has
   been reported to be involved in lipid metabolism, glycolipid assembly
   and possibly implicated in pathogenesis [[73]27] was also expressed in
   Mtb:ΔdosS infected samples ([74]Fig 3) and intraphagosomal in-vitro
   [[75]23], TBDB database, [76]http://www.tbdb.org). Although, we could
   not detect any lipid metabolism genes in Mtb:ΔdosT dataset, it has been
   suggested that host lipids are important sources of carbon and
   cholesterol required for ATP production in hostile environment [[77]28,
   [78]29]. These observations support our previous findings [[79]11] when
   numerous cholesterol clefts were present in mouse lungs infected with
   Mtb and mutant groups.

PE/PPE family

   The PE and PPE genes are unique to mycobacteria and are widely
   speculated to play a key role in tuberculosis pathogenesis [[80]30,
   [81]31]. We examined these genes in all datasets. In WT Mtb, PPE26
   (Rv1789) was induced to 1.8 fold, which plays an important role in
   protective immunity [[82]32] while p27 (Rv2108, 1.8 fold induction) is
   in sync with Th1 response against Mtb infection [[83]33]. Similarly
   PE15 (Rv1386, 1.9 fold induction) is involved in host-pathogen
   interactions that modulate innate immunity and mediate Mtb survival in
   macrophages [[84]34]. In Mtb:ΔdosR, following genes were up regulated;
   Rv3812, 1.72 fold; Rv0915c, 1.75 fold; Rv1807, 1.85 fold; Rv1788, 1.94
   fold; Rv3345c, 4.4 fold. It has been reported that antigen MBT41
   encoded by Rv3812 induces Th1 immune response in C57BL/6 mice infected
   with Mtb [[85]35] and Rv0915c encodes a protective antigen possibly
   involved in the early control of infection (‘Tuberculist’).

   In Mtb:ΔdosS, we also detected PE/ PPE family genes. For example,
   Rv3873 (1.9 fold induction) plays an immunomodulatory role in
   regulating the pathophysiology of mycobacteria [[86]34] and Rv3021
   (induced to 2.0 fold) also expresses under hypoxia [[87]36] and
   reaeration [[88]37]. In Mtb:ΔdosT, Rv1790, a member of PE/PPE family of
   which function is unknown was upregulated.

Regulatory proteins

   We next examined the expression levels of two-component regulatory
   system genes implicated in bacterial virulence in-vivo. In Mtb,
   senX3-regX3 two-component system is involved in the virulence [[89]38,
   [90]39]. Amongst members of this regulon, transcriptional regulator
   genes Rv2488c, Rv3060c and Rv1267c were expressed in the lungs of mouse
   infected with wild type Mtb only. Rv3060c encodes a fatty acid
   metabolism regulator (FadR) probably known to regulate the isocitrate
   lyase (ICL), which may enhance the bacterial survival and persistence
   in-vivo [[91]40, [92]41]. On the other hand Rv1267c (encodes EmbR) is
   involved in regulation of biosynthesis of the mycobacterial cell wall
   (Tuberculist). We also noted the expression of mce3R (Rv1963c, 1.8 fold
   induction), which plays a key a role in the adaptation and survival of
   Mtb in-vivo [[93]42]. In Mtb:ΔdosR, several regulatory protein family
   genes, for example, Rv1129c (1.8 fold induction) required for
   intracellular growth in macrophages [[94]43], Rv1151c (2.5 fold
   induction) required for intracellular cAMP signaling pathway [[95]44]
   were detected. The cAMP signaling plays a role in the interaction of
   mycobacteria with macrophages during infection [[96]45]. Similarly,
   Rv0890c induced to 2.3 fold is an Lrp/AsnC (leucine-responsive
   regulatory protein/asparagine synthase C) family transcriptional factor
   probably required for survival during persistence [[97]46] and Rv1103c
   (1.6 fold induction) is involved in pathogenesis [[98]47]. In Mtb:ΔdosS
   dataset, Rv2779c, an Lrp/AsnC transcriptional regulator known to be
   involved in various metabolic processes including starvation [[99]48],
   Rv0328 (1.6 fold induction) is also reported to be expressed during
   growth in NRP state [[100]24] and thioridazine [[101]49]. In this part
   of analysis pknJ (Rv2088, 1.5 fold induction) encoding a transmembrane
   serine/threonine-protein kinase also expresses during hypoxia [[102]36,
   [103]37], re-aeration [[104]37] and intraphagosomal environment
   [[105]23]. In particular, many of the genes required for bacterial
   persistence e.g. Rv2919c and Rv0744c [[106]7], Rv2989 [[107]50], Rv0405
   [[108]51], Rv3281 [[109]52] etc., down-regulated in Mtb:ΔdosS dataset
   may indicate growth restriction in mouse lungs ([110]Fig 2). These
   results also support our previous findings that Mtb:ΔdosS is attenuated
   in C3HeB/FeJ mice [[111]11]. In Mtb:ΔdosT dataset, Rv0465c was induced
   whose expression is high following the nutritional stress [[112]53] and
   Rv0386 encoding adenyl cyclase induced to 2.2 fold, is reported to be
   involved in virulence and may facilitate long-term intracellular
   survival of mycobacteria [[113]54].

Virulence, detoxification, adaptation

   Various genes involved in virulence, detoxification and adaptation were
   examined next. In Mtb, mce4A (Rv3499c) required for persistent
   tubercular infection [[114]55] was expressed to higher levels (1.8 fold
   induction). mce4A is a member of kstR (Rv3574) regulon and is involved
   in lipid catabolism [[115]56]. Another gene mce1A (Rv0169) involved in
   host cell invasion by Mtb and survival in human macrophages [[116]55]
   was expressed in Mtb dataset (1.65 fold induction). Similarly,
   induction of Rv1996 (1.8 fold), a member of DosR regulon may indicate
   the persistent infection [[117]13, [118]57]. In Mtb:ΔdosR following
   genes; Rv3358c, Rv2757c, Rv2596 and Rv1103c which have not been studied
   in details but belonging to virulence, detoxification and adaptation
   functional category were upregulated. In Mtb:ΔdosS, vapC36 (Rv1982c)
   upregulated to 2.9 fold also reported to be induced under stress
   conditions such as diamide [[119]58] and hypoxia [[120]36]; vapB33
   (Rv1241, 1.9 fold induction) also expresses under hypoxia [[121]36] and
   inside macrophages [[122]23]; vapb17 (Rv2526, 1.8 fold induction) also
   expresses under hypoxia [[123]36], reaeration [[124]37] and upon
   exposure to 0.05% SDS [[125]59]; ephG (Rv2740, 1.6 fold induction),
   involved in detoxification following oxidative damage to lipids, is
   also shown to be expressed during non replicative persistence
   (bacteriostatic) [[126]24]. In Mtb:ΔdosT, induction of Rv2190c (1.7
   fold) indicates involvement in pathogenicity as it is required for full
   virulence of Mtb in mice [[127]60] and Rv3417c, a chaperon associated
   with nucleoid [[128]61], may play a role in DNA supercoiling,
   macromolecular crowding etc. required during hostile environment. proV
   (Rv3758c, 2.0 fold induction) mRNA levels were increased in Mtb:ΔdosT
   infected mouse lungs. ‘proV’ is involved in osmoregulation as bacteria
   in the phagosome begin to grow and has been shown to increase during
   post-phagocytosis in cultured human macrophages [[129]62] and in lungs
   of mice infected with Mtb [[130]63].

Pathways analyses in-vivo

   To understand the functional relevance of mycobacterial genes expressed
   during infection, we used IntPath database [[131]50] for pathway
   enrichment analysis and the enriched (over-represented) functional
   categories that are closely related to both pathogen growth and
   infection were compared. We were able to identify various pathways
   representing one or more functional category such as cell wall and cell
   processes, information pathways, intermediary metabolism, lipid
   metabolism, PE/PPE family, regulatory proteins and ‘virulence,
   detoxification, adaptation’ in all datasets ([132]S2 Table). Most of
   these pathways were differentially expressed in Mtb vs. Dos mutants
   during growth in mouse lungs. For example, information pathways e.g.
   “DNA mismatch repair”, “RNA polymerase” ([133]S1 Fig) and pathways
   belonging to lipid metabolism e.g. “Lipopolysaccharide biosynthesis”,
   "2-Oxobutanoate Degradation I", Carbon fixation pathways in
   prokaryotes, ([134]S2 Fig) and intermediary metabolism pathways e.g.
   Antigen biosynthesis, sugar metabolism (glycolysis, gluconeogenesis,
   pyruvate phosphate pathways etc.), superpathways of chorismate, amino
   acid biosynthesis ([135]S3 Fig) were significantly changed in mice
   lungs infected with Mtb. In Mtb:ΔdosR, pathways such as “Guanosine
   nucleotides de novo pathway of methionine biosynthesis, superpathway of
   amino acids biosynthesis, nucleotide biosynthesis, TCA cycle, NAD
   phosphorylation, etc. were significantly changed ([136]S1–[137]S3
   Figs). On the other hand, Mtb:ΔdosS exhibited significantly different
   pathways changed in mouse lungs. Specifically serine-isocitrate lyase
   pathway, tryptophan degradation VII (via indole-3-pyruvate) tyrosine
   biosynthesis I, Inositol phosphate metabolism, glutamate metabolism,
   Taurine and hypotaurine metabolism, TCA cycle, nitrogen metabolism in
   addition to pathways related to metabolism and respiration etc.
   ([138]S1–[139]S3 Figs). The mutant Mtb:ΔdosT exhibited following
   pathways; arginine biosynthetic pathways, citrulline metabolism,
   enterobactin biosynthesis, urea cycle in addition to metabolic
   pathways, nicotinamide metabolism, ([140]S1 and [141]S3 Figs). The
   sulfur relay system pathway involved in cellular functions such as cell
   proliferation, apoptosis and DNA repair [[142]64] was changed in both
   Mtb and Mtb:ΔdosT.

   Mtb is able to grow on variety of carbon sources, but uses fatty acids
   as the major sources of carbon and energy essential for its growth
   during infection [[143]65]. In summary, these pathways are closely
   related to TCA cycle ([144]S1–[145]S3 Figs), which is essential for the
   growth of Mtb growth and metabolism [[146]65].

Mycobacterial gene expression in Mtb and Dos mutants in mouse lungs

   We also applied a hierarchical clustering algorithm [[147]11, [148]66]
   to group the genes by expression patterns (down-, up-regulated or
   no-change in gene expression) that may reflect similar function once
   the bacilli establish the infection and persist in mouse lungs.
   Hierarchical clustering supported the gene classes belong to functional
   categories derived from ‘Tuberculist’ ([149]Fig 4). We grouped eight
   such clusters from all four groups and these represent the genes highly
   expressed in more than one dataset, confirming their requirement in
   C3HeB/FeJ mouse lungs (this study) and BALB/c mice [[150]7]. These
   clusters included the genes belonging to functional categories such as
   information pathways, lipid metabolism, immunomodulation, virulence,
   etc. required for survival or persistence. Following to gene expression
   pattern, the reduction in bacillary load of Mtb:ΔdosS in C3HeB/FeJ
   mouse lungs ([151]Fig 2), ref. [[152]11]) thus be explained and
   probably indicates the role of following genes in survival of bacilli;
   for example, the transcriptional regulator glnB (Rv2919c) required for
   survival of bacilli in mice [[153]7] and macrophages [[154]67] was
   up-regulated in Mtb but down-regulated in Mtb:ΔdosS infected samples
   indicate its importance in survival ([155]Fig 2). Another gene, Rv2989
   required for survival in macrophages [[156]50] and during hypoxia
   [[157]36] was down-regulated in Mtb:ΔdosS infected samples only
   ([158]Fig 4). Similarly, Rv0744c which upregulates during hypoxia
   [[159]36] and in mice [[160]7] was downregulated in Mtb:ΔdosS samples
   ([161]Fig 4), again indicates its role in Mtb survival. Similarly
   Rv0405 required for bacterial resistance in mice [[162]51] and Rv3281
   for growth and pathogenesis [[163]52], were down-regulated in Mtb:ΔdosS
   infected samples. However, Rv0045c, a serine hydrolase enzyme possibly
   required for transition between dormant and active Mtb infection
   [[164]26] and Rv0166 necessary for the persistence in murine model
   [[165]68] were not altered in gene expression during Mtb:ΔdosS growth
   in mice ([166]Fig 4).

Fig 4. Hierarchical clustering of Mtb genes expressed in C3HeB/FeJ mouse
lungs.

   [167]Fig 4
   [168]Open in a new tab

   Hierarchical clustering demonstrates the expression of common genes
   (low, blue to high, orange) in two or more datasets in C3HeB/FeJ mice.
   The data was compared to functional categories of Mtb genes described
   in the ‘Tuberculist’ database.

   The expression of Rv3585 gene encoding the DNA repair protein ‘RadA’
   (Tuberculist) indicates that recombination of genes may occur during
   mycobacterial growth at these time points. We did not detect the ‘radA’
   levels in Mtb:ΔdosS dataset. DNA microarray analysis also lead us to
   the identification of variety of other genes that code for the proteins
   like putative transporters e.g. Rv0283, Rv2320c, Rv1686c etc. and
   membrane protein Rv1671, Rv0954, Rv0426c etc. whose expression were
   either upregulated or did not change during course of infection. The
   sigma factor sigL dependent transcription of Rv2877c that is believed
   to be important in Mtb pathogenesis [[169]69] was also noted in Mtb WT
   dataset.

   The genes belong to succinate metabolism are important for adaptation
   of Mtb to hypoxia [[170]70]. For example DctA, a
   C4-dicarboxylate-transport transmembrane protein important for
   translocation of TCA cycle intermediates e.g. Succinate, fumarate or
   malate to Mtb were either upregulated (Mtb and Mtb:ΔdosR) or their
   expression levels were unchanged during course of infection in all
   dataset. Rv2443 levels have been shown to be upregulated during hypoxia
   in-vitro [[171]24] and in mice [[172]7].

   At the same time different sets of genes whose function is conserved
   were expressed in all datasets e.g. members of the toxin-antitoxin
   system involved in virulence, detoxification and adaptation
   (vapB32/Rv1113, mce3R/Rv1963c, Rv0959, Rv3189 in Mtb WT); Rv3181c,
   vapB46/Rv3385c, Rv3749c, vapC21/Rv2757c, vapC40/Rv2596, mazE3/Rv1103c
   in Mtb:ΔdosR; vapC36/Rv1982c, vapC36/Rv1982c, vapB33/Rv1241,
   vapB17/Rv2526 in Mtb:ΔdosS; Rv0060, vapC13/Rv1838c in Mtb:ΔdosT
   ([173]S1 Table). Similarly, genes changed in hypoxia in-vitro
   experiments [[174]13, [175]24] were also detected in mouse lungs
   datasets ([176]S3 Table). The hypoxia responsive genes may contribute
   to establishment of persistent infection during host environment. The
   upregulation of dosR regulon genes e.g. Rv0569, Rv1996, Rv0571c, Rv2004
   in mouse lungs ([177]S3 Table) indicate that bug experiences the stress
   such as hypoxia [[178]13, [179]24] in hostile environment.

Insights gained from comparison to previous genome-wide expression studies

   We performed a comparative transcriptomics analysis of our datasets
   (genes detected in chronic phase of infection) with data obtained from
   BALB/c mice (early time point) ([180]Fig 5A), ref. [[181]7],
   macrophages ([182]Fig 5B), ref. [[183]23] and in-vitro (NRP) conditions
   (Figs [184]6 and [185]7), ref. [[186]24]. Functional grouping of genes
   based on gene expression profile demonstrated similarity or
   dissimilarity among various datasets (Figs [187]5 and [188]6 and
   [189]S1, [190]S3, [191]S4, [192]S5 Tables). Of note Rv0961, Rv0971c,
   Rv0966c, Rv0963c, Rv0974c, Rv0975c, Rv0976c and Rv0996 of iVEGI
   (in-vivo expressed genomic island) signature in BALB/c mice [[193]7],
   were also detected in our datasets (Fig [194]5A and [195]6 and [196]S4
   Table).

Fig 5. Scatter plot diagram showing similarity and dissimilarity in gene
expression from various datasets.

   [197]Fig 5
   [198]Open in a new tab

   A). Comparison of gene expression in C3HeB/FeJ mouse lungs infected
   with Mtb strains (red- Mtb; black- Mtb:ΔdosR; blue- Mtb:ΔdosS; green-
   Mtb:ΔdosT) versus gene expression profile in BALB/c mice [[199]7] B).
   Graph shows the bacterial genes and their expression levels in
   C3HeB/FeJ mouse lungs (this study) compared to infected macrophages at
   4- and 24-hr post infection [[200]23].

Fig 6. Validation of Mtb gene expression in mouse lungs by quantitative
RT-PCR.

   Fig 6
   [201]Open in a new tab

   The expression of indicated genes in intracellular bacteria was
   compared to that of bacteria growing exponentially in 7H9 broth by
   RT-PCR. The expression of each gene was normalized to sigA and fold
   change were calculated from three biological replicates.

Fig 7. Hierarchical clustering of bacterial genes expressed in C3HeB/FeJ
mouse lungs.

   [202]Fig 7
   [203]Open in a new tab

   A snapshot of few bacterial genes induced in C3HeB/FeJ mouse lungs upon
   infection with Mtb or Mtb:ΔdosR or Mtb:ΔdosS or Mtb:ΔdosT and their
   comparison with genes expressed during NRP [[204]24] is shown. A
   gradual decrease or increase in color intensity indicates low (blue) or
   high (orange) expression. For example, a gradual increase in gene
   expression over 80 days of hypoxia indicates their requirement during
   both hypoxia in-vitro and chronic phase of infection in C3HeB/FeJ mouse
   lungs.

   Similarly, an overlap in genes C3HeB/FeJ mouse lungs (this study) vs.
   macrophages ([205]Fig 5B and [206]S5 Table), ref [[207]23] indicates
   their requirement not only in macrophages ex-vivo but also in- vivo.
   For example, clpX gene required for stress tolerance [[208]71] and
   bacterial growth [[209]72] was upregulated in our datasets ([210]S5
   Table). An comparison with ‘NRP’ dataset [[211]24] also showed an
   overlap of array of genes e.g. Rv2122c, Rv0045c, Rv0630c etc. ([212]S3
   Table). Rv2122c encodes a phosphoribosyl-ATP pyrophosphohydrolase,
   required for the growth of Mtb and is a member of ideR (iron-dependent
   regulator), probably involved in virulence [[213]73]. The transition
   between dormant and active Mtb infection requires reorganization of
   lipid metabolism and activation of a battery of serine hydrolase
   enzymes such as Rv0045c [[214]74]. We found upregulation of Rv0045c in
   our datasets that might indicate transition in state of bacilli within
   host. The perturbation of Rv0630c indicates modification of Mtb genes
   in hostile environment [[215]54]. Similarly, upregulation of radA
   (Rv3585, encodes a DNA repair protein) and Rv3417c expressions indicate
   DNA modifications during in-vivo growth (Tuberculist) and interactions
   with Toll like Receptors respectively [[216]75] ([217]S3 Table).
   Hierarchical clustering demonstrated an overlap in genes expressed on
   C3HeB/FeJ mouse lungs (this study) vs. in-vitro (NRP) conditions
   ([218]Fig 7). We grouped the time points NRP day-6, -10, -14, 30, and
   -80. We considered the time point NRP day 80 since this represents
   long-term hypoxia. A gradual increase in gene expression over 80 days
   of hypoxia indicates their requirement during both hypoxia in-vitro and
   chronic phase of infection in C3HeB/FeJ mouse lungs. In Mtb:ΔdosR, the
   upregulation of Rv0890c, Rv048c, Rv1515c, Rv1218c etc. in C3HeB/FeJ
   mouse lungs and gradual decrease in expression of these genes over 80
   days of hypoxia indicates their requirement in chronic phase of
   infection only. Similarly in Mtb:ΔdosS, a gradual decrease in
   expression of Rv2585c, Rv0633c, Rv1005c, Rv2122c etc. over 80 days of
   long-term hypoxia indicate their requirement in chronic phase of
   infection only. In Mtb:ΔdosT both, upregulated (Rv3236c, Rv0311,
   Rv0465c, Rv2044c etc.) and down-regulated (Rv0045c, Rv3758c, Rv0937c,
   Rv0060 etc.) genes over 80 days of hypoxia indicate differential gene
   expression compared to C3HeB/FeJ mouse.

   The comparative analysis reveals an overlap in many of the genes and
   their expression levels between C3HeB/FeJ and BALB/c mice, which
   clearly indicates that these genes are required during both early
   [[219]7]) and chronic phase (this study) of infection. Similarly, an
   overlap in gene expression between C3HeB/FeJ and macrophage or NRP
   conditions indicated their requirement both during in-vivo and
   in-vitro.

Discussion

   The outcome of the host-pathogen interactions is in large part shaped
   by selective gene expression during infection [[220]76]. Thus,
   bacterial gene expression during course of infection has the potential
   to provide specific and key knowledge about the physiology og the
   pathogen within its intra-granulomatous niche. It is conceivable that
   this information will generate a list of in-vivo druggable targets of
   chemotherapy, which may be otherwise ignored.

   Thus, here, we describe the gene expression profile of Mtb strains viz.
   Mtb, Mtb:ΔdosR, Mtb:ΔdosS and, Mtb:ΔdosT in the human-like lung lesions
   of C3HeB/FeJ mice. In particular, Mtb:ΔdosS is primarily focused. The
   data presented here provide important new information about the
   adaptation of this pathogen inside the host with co-expression of
   similar ([221]Fig 4) or unique ([222]Fig 3) genes being detected among
   these groups. Thus, for example, the co-expression of following genes
   viz. Rv2488c, Rv3060c, Rv1129c, Rv0890c, Rv0328, Rv2088, Rv0465c in the
   functional category ‘response regulator’ highlights their importance in
   regulating gene expression during in-vivo growth. Specifically Rv0465c
   encodes a transcription factor designated RamB [[223]77], which is a
   key regulator of isocitrate lyase and glyoxylate shunt, a metabolic
   pathway critical for Mtb persistence [[224]78]. The expression of RamB
   appears to be regulated by the SigE/SigB regulatory axis [[225]77],
   which is itself regulated by SigH [[226]22, [227]58, [228]79], PknB
   [[229]80], ClgR [[230]81, [231]82] and other regulatory loops, many of
   which are known to be induced during macrophage infection as well as
   in-vivo [[232]23, [233]83]. The SigH/SigE/SigB/ClgR regulatory circuit
   is critical for the pathogen to face the host oxidative burst and
   required for initial infectivity in primate lungs [[234]84]. It appears
   that this network is responsible for evasion of antibacterial responses
   leading to the prolonged survival of Mtb [[235]85].

   Similarly, Rv2088 encodes for a protein kinase PknJ, which is also
   induced in the lungs of guinea pigs infected with Mtb [[236]86]. Among
   the various targets that PknJ is experimentally known to phosphorylate
   and activate [[237]87], EmbR is a transcriptional factor required for
   the expression of the embCAB operon, that encodes the critical cell
   wall arabinosyl transferases [[238]88]. This pathway is important for
   both the acquisition of resistance to ethambutol (a frontline
   antimycobacterial drug) and the cell wall Lipoarabinomannan/Lipomannan
   ratio (that plays a key role in immune-evasion). Another known PknJ
   target is the methyl transferase MmaA4/Hma, which is involved in
   mycolic acid biosynthesis.

   The expression of the transcription factor Rv0328 also appears to be
   governed by the SigH/SigE/SigB axis [[239]23, [240]49] indicating a
   role in both immune evasion and pathogenesis. Rv1129c encodes a
   transcription factor that is essential for the induction of the
   propionyl-CoA assimilating methyl citrate cycle enzymes [[241]43],
   which are required for both intra-phagosomal survival of Mtb as well as
   for survival on cholesterol-containing media (which is a key carbon
   source for Mtb during intra-phagosomal persistence in lungs [[242]89],
   as well as for the catabolism of cholesterol [[243]43]. Rv1129c is also
   known to be dependent upon SigE for its expression [[244]77]. Rv2488c
   encodes a transcription factor that is also known to be induced in
   guinea pig lungs [[245]86], and is predicted to be in the SenX3/RegX3
   network [[246]38], critical for defense against damage to DNA, which is
   experienced by Mtb during oxidative stress in-vivo [[247]90, [248]91].
   Thus, transcriptomics analysis of Mtb derived from human-like caseous
   lungs lesions in C3HeB/FeJ mice at chronic stage paints a picture where
   the pathogen experiences diverse stress conditions including but not
   limited to oxidative stress, hypoxia, adaptation to less-preferred
   carbon and nitrogen sources aka cholesterol, and damage to
   cell-surface, DNA and lipids. Hence, gene-expression modules controlled
   by these regulators represent important in-vivo targets.

   Lipid metabolism plays a key role in the Mtb pathogenesis during which
   bacilli use fatty acids as a sole carbon source for the survival
   in-vivo [[249]43]. In addition, cell wall lipids play variety of roles
   in physiology and pathogenesis during infection [[250]92]. Many of the
   genes involved in lipid metabolism, critical in the cell membrane
   biosynthesis, sugar metabolism, bacterial resistance within host,
   survival, immunomodulation and pathogenesis could be detected in all
   datasets. This strongly suggests the requirement of modified lipid
   metabolism in-vivo, as has been postulated and studied by others
   [[251]26, [252]93, [253]94]. Recently we have reported that Mtb:ΔdosS
   is attenuated in Kramnik mice [[254]11] we, therefore, predicted that
   the attenuation of Mtb:ΔdosS mutant may results from lack of expression
   of bacterial genes required for survival and persistence during
   infection. Following genes required for survival in mice and
   macrophages were downregulated in Mtb:ΔdosS dataset; glnB (Rv2919c)
   [[255]7, [256]67], Rv2989 [[257]50] Rv0744c [[258]7, [259]51] Rv2989
   [[260]50], Rv0405 (38) and Rv3281 [[261]52].

   Several other genes highly expressed in-vivo, including genes that were
   shown to be involved in cell wall biosynthesis (e.g. Rv1350, Rv3840c,
   Rv3895c etc.), transcriptional regulation (e.g. Rv2488c, Rv2799c,
   Rv0329 etc.) may contribute to the establishment of the infection
   inside the host. Moreover, we detected differentially expressed genes
   in all datasets (96–98% genes were unique). A set of 650 genes in Mtb;
   255 genes in Mtb:ΔdosR, 406 genes in Mtb:ΔdosS, 114 genes in Mtb:ΔdosT
   ([262]Fig 1) were expressed in C3HeB/FeJ mice with at least 36 and not
   more than 53 genes were common in all datasets. The pathways
   significantly changed in Mtb, Mtb:ΔdosR, Mtb:ΔdosS or Mtb:ΔdosT during
   growth in C3HeB/FeJ mice lungs were information-, intermediary-, and
   lipid metabolism-pathways ([263]S1–[264]S3 Figs). Genes such as fdxC
   (Rv1177) induces at low pH, DNA damage stress [[265]95], and during
   growth in macrophages [[266]96]. The list of the genes in our datasets
   ([267]S4 and [268]S5 Tables) and those induced in macrophages [[269]23]
   and BALB/c mice [[270]7] suggests that the host immune response after
   infection is characterized by macrophage activation.

   A change in the growth-dependent genes and their expression levels e.g.
   those belonging to information pathways and intermediary metabolism
   (different genes but from the same functional category among strains,
   [271]Fig 3) was observed. An analysis of the transcriptional response
   of Mtb genes in Kramnik mice observed in the present study suggests
   that protective functions are conserved which could facilitate the
   adaptation of Mtb in hostile environment. In summary, transcriptomics
   analysis of Mtb and Dos mutants also indicates both the macrophage-like
   and multiple stress environments that may influence the adaptation and
   affect the persistence of bacilli intracellularly.

Conclusions

   As part of this study we present our analysis of i) Mtb gene expression
   at the chronic stage of infection in the C3HeB/FeJ mouse model and ii)
   present comparisons with the various mutants in the hypoxia-sensing
   regulon controlled by the DosR transcription factor. The expression of
   iVEGI genes [[272]7] in our datasets indicates their requirement not
   only during onset (and the early stages) of Mtb infection but also
   their significant contribution during the chronic stages. In addition,
   our analysis identified both core gene sets and core categories which
   were present in all datasets, as well as specific genes which correlate
   with the relative attenuation of the Mtb:ΔdosS mutant in this mouse
   model. Several of these genes are important for lipid metabolism as
   well as for survival in the wake of diverse host-generated stress
   conditions such as hypoxia, oxidative stress, DNA damage, lack of
   availability of preferred carbon sources etc. These findings have the
   potential to allow us to better understand the dynamics of bacilli in
   C3HeB/FeJ mice that mimic the pathology of human lung granuloma and may
   provide the information for possible drug and/ or vaccine targets.
   Further, more in-depth studies are required to better understand as to
   how these gene signatures correspond to bacterial virulence or control
   of infection.

Ethics Statement

   All the animal samples used as part of this study were generated in a
   previous study, which was entirely approved, by the Tulane National
   Primate Research Centre (TNPRC) Institutional Animal Care and Use
   Committee (IACUC) as a protocol, which was submitted by the Principal
   Investigator.

Supporting Information

   S1 Fig. Integration of functional category ‘information pathways’ and
   its group percentage.

   The results obtained are based on an overlap between the total numbers
   of genes changed in each of the biological replicate of mice lung
   samples to the genes in a functional category assigned in Tuberculist.
   These numbers were then used to calculate group percentage for
   functional category ‘information pathway’, changed in Mtb or Dos
   mutants in mouse lung using IntPath [[273]50].

   (TIF)
   [274]Click here for additional data file.^ (510.8KB, tif)
   S2 Fig. Integration of functional category lipid metabolism and its
   group percentage.

   The results summarize the group percentage for functional category
   ‘lipid metabolism pathways’ based on an overlap between the total
   numbers of genes changed in each of the biological replicate of mice
   lung samples to the genes in the functional category ‘lipid metabolism’
   assigned in Tuberculist.

   (TIF)
   [275]Click here for additional data file.^ (999KB, tif)
   S3 Fig. Integration of functional category intermediary metabolism and
   its group percentage.

   The group percentage was calculated based on an overlap between the
   total numbers of genes changed in each of the biological replicate of
   mice lung samples to the genes in functional category ‘intermediary
   metabolism’ assigned in Tuberculist.

   (TIF)
   [276]Click here for additional data file.^ (2.2MB, tif)
   S1 Table. Functional categories and their genes changed in Mtb- or Dos
   mutants-infected mouse lung samples.

   The Table summarizes genes identified in various functional categories
   based on the information available in the ‘Tuberculist’ database for
   Mtb H37Rv genome.

   (XLS)
   [277]Click here for additional data file.^ (534KB, xls)
   S2 Table. Enriched biological pathways changed in mouse lungs.

   Various pathways representing one or more functional category as per
   Tuberculist and IntPath [[278]50] database are shown.

   (XLS)
   [279]Click here for additional data file.^ (37KB, xls)
   S3 Table. List of genes associated with bacterial persistence.

   The Table summarizes hypoxia responsive genes changed in C3HeB/FeJ
   mouse lungs (this study) versus in-vitro conditions [[280]24].

   (XLS)
   [281]Click here for additional data file.^ (1.2MB, xls)
   S4 Table. Bacterial gene expression in C3HeB/FeJ mouse lungs.

   Comparison of genes and their expression in C3HeB/FeJ mice lungs
   infected with Mtb strains (Mtb, Mtb:ΔdosR, Mtb:ΔdosS, Mtb:ΔdosT) versus
   genes expressed in Mtb infected BALB/c mice lungs [[282]7].

   (XLS)
   [283]Click here for additional data file.^ (353KB, xls)
   S5 Table. Biological pathways changed in Mtb or Dos mutants infected
   mouse lungs.

   *The Table summarizes enriched pathways significantly changed (P<0.05)
   in mouse lungs infected with Mtb or Mtb:ΔdosR or Mtb:ΔdosS or Mtb:ΔdosT
   relative to in-vitro grown cultures. The ‘p-value’ for a pathway is
   based on IntPath database that uses hyper-geometric test to find most
   significant pathways in an input gene list to the number of genes
   assigned for a functional category in the genome [[284]50].

   (XLS)
   [285]Click here for additional data file.^ (426KB, xls)

Acknowledgments